dlmSmooth {dlm} | R Documentation |
The function apply Kalman smoother to compute smoothed values of the state vectors, together with their variance/covariance matrices.
dlmSmooth(modFilt, debug = FALSE)
modFilt |
An object of class "dlmFiltered" , such as returned by
dlmFilter |
debug |
If FALSE , faster C code will be used, otherwise
all the computations will be performed in R. |
The calculations are based on the singular value decomposition (SVD) of the relevant matrices. Variance matrices are returned in terms of their SVD.
A list with components
s |
Time series (or matrix) of smoothed values of the state vectors. The series starts one time unit before the first observation. |
U.S |
See below. |
D.S |
Together with U.S , it gives the SVD of the variances
of the smoothing errors. |
Giovanni Petris, <GPetris@uark.edu>
Zhang, Y. and Li, X.R., Fixed-interval smoothing algorithm based on singular value decomposition, Proceedings of the 1996 IEEE International Conference on Control Applications.
See dlm
for a description of dlm objects,
dlmSvd2var
to obtain a variance matrix from its SVD,
dlmFilter
for Kalman filtering,
dlmMLE
for maximum likelihood estimation, and
dlmBSample
for drawing from the posterior distribution
of the state vectors.
### See example for dlmFilter